10 citations · 32 across the 8 of their papers we have counts for
Showing 2023Show all
3 papers · 1 filter
cs.CV2023★ 4 cited
Module-wise Adaptive Distillation for Multimodality Foundation Models
Chen Liang, Jiahui Yu, Ming-Hsuan Yang +5
Pre-trained multimodal foundation models have demonstrated remarkable generalizability but pose challenges for deployment due to their large sizes. One effective approach to reduci…
cs.CV2023★ 10 cited
DaTaSeg: Taming a Universal Multi-Dataset Multi-Task Segmentation Model
Xiuye Gu, Yin Cui, Jonathan Huang +8
Observing the close relationship among panoptic, semantic and instance segmentation tasks, we propose to train a universal multi-dataset multi-task segmentation model: DaTaSeg.We u…
cs.CV2023★ 1 cited
Towards Understanding the Effect of Pretraining Label Granularity
Guan Zhe Hong, Yin Cui, Ariel Fuxman +2
In this paper, we study how the granularity of pretraining labels affects the generalization of deep neural networks in image classification tasks. We focus on the "fine-to-coarse"…